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  • βœ‡Omics In Lung
  • AI in multi-omics analysis in obstructive lung diseases Paramita Roy Β· Sudipto Saha
    Prog Mol Biol Transl Sci. 2026;222:165-206. doi: 10.1016/bs.pmbts.2026.01.025. Epub 2026 Mar 2.ABSTRACTThe reports of obstructive lung diseases (OLDs) like asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis show increasing global prevalence. The available treatment options for these diseases are limited to antibiotics and steroids. Different multi-omics integration approaches have been applied in studying host, microbiome, and host-microbiome interactions in these diseases
     

AI in multi-omics analysis in obstructive lung diseases

22 May 2026 at 18:00

Prog Mol Biol Transl Sci. 2026;222:165-206. doi: 10.1016/bs.pmbts.2026.01.025. Epub 2026 Mar 2.

ABSTRACT

The reports of obstructive lung diseases (OLDs) like asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis show increasing global prevalence. The available treatment options for these diseases are limited to antibiotics and steroids. Different multi-omics integration approaches have been applied in studying host, microbiome, and host-microbiome interactions in these diseases to get better insights. Artificial intelligence (AI)-based, as well as statistical and other approaches, are used for multi-omics analyses, specifically the integration of multi-omics data in OLDs. This chapter discusses various aspects of multi-omics integration studies in asthma, COPD, and bronchiectasis. Overall, these studies focused on disease subtype classification, risk assessment, association with genetic factors, and several other aspects.

PMID:42173629 | DOI:10.1016/bs.pmbts.2026.01.025

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